§1.1 Field of the Invention
The present invention concerns advertising. In particular, the present invention concerns improving content-targeted advertising.
§1.2 Related Art
Advertising using traditional media, such as television, radio, newspapers and magazines, is well known. Unfortunately, even when armed with demographic studies and entirely reasonable assumptions about the typical audience of various media outlets, advertisers recognize that much of their ad budget is simply wasted. Moreover, it is very difficult to identify and eliminate such waste.
Recently, advertising over more interactive media has become popular. For example, as the number of people using the Internet has exploded, advertisers have come to appreciate media and services offered over the Internet as a potentially powerful way to advertise.
Advertisers have developed several strategies in an attempt to maximize the value of such advertising. In one strategy, advertisers use popular presences or means for providing interactive media or services (referred to as “Websites” in the specification without loss of generality) as conduits to reach a large audience. Using this first approach, an advertiser may place ads on the home page of the New York Times Website, or the USA Today Website, for example. In another strategy, an advertiser may attempt to target its ads to more narrow niche audiences, thereby increasing the likelihood of a positive response by the audience. For example, an agency promoting tourism in the Costa Rican rainforest might place ads on the ecotourism-travel subdirectory of the Yahoo Website. An advertiser will normally determine such targeting manually.
Regardless of the strategy, Website-based ads (also referred to as “Web ads”) are often presented to their advertising audience in the form of “banner ads”—i.e., a rectangular box that includes graphic components. When a member of the advertising audience (referred to as a “viewer” or “user” in the Specification without loss of generality) selects one of these banner ads by clicking on it, embedded hypertext links typically direct the viewer to the advertiser's Website. This process, wherein the viewer selects an ad, is commonly referred to as a “click-through” (“Click-through” is intended to cover any user selection.). The ratio of the number of click-throughs to the number of impressions of the ad (i.e., the number of times an ad is displayed or otherwise rendered) is commonly referred to as the “click-through rate” or “CTR” of the ad.
A “conversion” is said to occur when a user consummates a transaction related to a previously served ad. What constitutes a conversion may vary from case to case and can be determined in a variety of ways. For example, it may be the case that a conversion occurs when a user clicks on an ad, is referred to the advertiser's Web page, and consummates a purchase there before leaving that Web page. Alternatively, a conversion may be defined as a user being shown an ad, and making a purchase on the advertiser's Web page within a predetermined time (e.g., seven days). In yet another alternative, a conversion may be defined by an advertiser to be any measurable/observable user action such as, for example, downloading a white paper, navigating to at least a given depth of a Website, viewing at least a certain number of Web pages, spending at least a predetermined amount of time on a Website or Web page, etc. Often, if user actions don't indicate a consummated purchase, they may indicate a sales lead, although user actions constituting a conversion are not limited to this. Indeed, many other definitions of what constitutes a conversion are possible. The ratio of the number of conversions to the number of impressions of the ad (i.e., the number of times an ad is displayed or otherwise rendered) is commonly referred to as the conversion rate. If a conversion is defined to be able to occur within a predetermined time since the serving of an ad, one possible definition of the conversion rate might only consider ads that have been served more than the predetermined time in the past.
The hosts of Websites on which the ads are presented (referred to as “Website hosts” or “ad consumers”) have the challenge of maximizing ad revenue without impairing their users' experience. Some Website hosts have chosen to place advertising revenues over the interests of users. One such Website is “Overture.com,” which hosts a so-called “search engine” service returning advertisements masquerading as “search results” in response to user queries. The Overture.com Website permits advertisers to pay to position an ad for their Website (or a target Website) higher up on the list of purported search results. If such schemes where the advertiser only pays if a user clicks on the ad (i.e., cost-per-click) are implemented, the advertiser lacks incentive to target their ads effectively, since a poorly targeted ad will not be clicked and therefore will not require payment. Consequently, high cost-per-click ads show up near or at the top, but do not necessarily translate into real revenue for the ad publisher because viewers don't click on them. Furthermore, ads that viewers would click on are further down the list, or not on the list at all, and so relevancy of ads is compromised.
Search engines, such as Google for example, have enabled advertisers to target their ads so that they will be rendered in conjunction with a search results page responsive to a query that is relevant, presumably, to the ad. The Google system tracks click-through statistics (which is a performance parameter) for ads and keywords. Given a search keyword, there are a limited number of keyword targeted ads that could be shown, leading to a relatively manageable problem space. Although search result pages afford advertisers a great opportunity to target their ads to a more receptive audience, search result pages are merely a fraction of page views of the World Wide Web.
Some online advertising systems may use ad relevance information and document content relevance information (e.g., concepts or topics, feature vectors, etc.) to “match” ads to (and/or to score ads with respect to) a document including content, such as a Web page for example. Examples of such online advertising systems are described in:                U.S. Provisional Application Ser. No. 60/413,536 (incorporated herein by reference), entitled “METHODS AND APPARATUS FOR SERVING RELEVANT ADVERTISEMENTS,” filed on Sep. 24, 2002 and listing Jeffrey A. Dean, Georges R. Harik and Paul Bucheit as inventors;        U.S. patent application Ser. No. 10/314,427 (incorporated herein by reference), entitled “METHODS AND APPARATUS FOR SERVING RELEVANT ADVERTISEMENTS,” filed on Dec. 6, 2002 and listing Jeffrey A. Dean, Georges R. Harik and Paul Bucheit as inventors;        U.S. patent application Ser. No. 10/375,900 (incorporated herein by reference), entitled “SERVING ADVERTISEMENTS BASED ON CONTENT,” filed on Feb. 26, 2003 and listing Darrell Anderson, Paul Bucheit, Alex Carobus, Claire Cui, Jeffrey A. Dean, Georges R. Harik, Deepak Jindal, and Narayanan Shivakumar as inventors; and        U.S. patent application Ser. No. 10/452,830 (incorporated herein by reference), entitled “SERVING ADVERTISEMENTS USING INFORMATION ASSOCIATED WITH E-MAIL,” filed on Jun. 2, 2003 and listing Jeffrey A. Dean, Georges R. Harik and Paul Bucheit as inventors.Generally, such online advertising systems may use relevance information of both candidate advertisements and a document to determine a score of each ad relative to the document. The score may be used to determine whether or not to serve an ad in association with the document (also referred to as eligibility determinations), and/or to determine a relative attribute (e.g., screen position, size, etc.) of one or more ads to be served in association with the document. The determination of the score may also use, for example, one or more of (1) one or more performance parameters (e.g., click-through rate, conversion rate, user ratings, etc.) of the ad, (2) quality information about an advertiser associated with the ad, and (3) price information (e.g., a maximum price per result (e.g., per click, per conversion, per impression, etc.)) associated with the ad.        
Many content owners (e.g., publishers of Web pages) who sell ad inventory on their Websites (or otherwise agree to have ads rendered on their Websites) do not want to display ads that compete with their product offerings. Some content owners have existing exclusive relationships with advertisers. Such content owners either do not want to display, or are contractually prohibited from displaying, ads that compete with their exclusive partner's product offerings. For example, a Website selling auto insurance may not want to show ads with links to other Websites selling auto insurance. Similarly, a Website with content related to flowers may have an exclusive relationship with a flower delivery company to show only its ads for flower delivery.
Some ad serving systems offer a URL-based or domain-based (e.g., Website based) ad blocking. In such systems, a block list includes URLs and/or Website home pages. Ads may include a visible URL or a link to a URL. If an ad includes a visible URL or a link to a URL that is on the block list associated with a particular Web page, it is not served with that Web page. Unfortunately, generating block lists often entails a highly manual process of generating related keywords and searching on those keywords to identify ads that should be blocked. Further, managing such block lists becomes difficult as new ads for new Web pages or Websites are added. Otherwise, the block list will not block new ads entered after the initial creation of the block list. Finally, block lists are often over-inclusive. For example, all ads on superstores like Amazon might be blocked when only a product category needs to be blocked. Thus, potential advertising revenue is lost.
Some ad serving systems, particularly those that serve ads targeted to terms of a search query, allow content owners to use a list of keywords, commonly referred to as “black lists,” to black out ads or block ads for a set of search terms competitive to the content owner or its exclusive partner. For example, America Online might want to block out ads targeted to the keyword “ISP.” Unfortunately, black lists do not work very well for content-based ad targeting since a Web page may be associated with multiple categories. Instead of eliminating all ads targeted to black listed keywords (e.g., flowers, roses, tulips, carnations, bouquet, baby's breath, . . . , or 1800access, USWest, Juno Online, . . . ), which entails an extensive list of keywords, it's best to just eliminate the ads for the offending category (e.g., flowers, or Internet service providers) and show other related ads. Thus, black lists have the problem of requiring manually generating a set of keywords pertaining to a category. Since these lists are often under-inclusive, particularly if they are not updated regularly, undesirable ads may be served on a content owner's document, resulting in lost good will. Indeed, this problem is more apparent content-based ad targeting partners than search-based keyword targeting partners, since ad slippage (i.e., the rendering of an ad that should be blocked) is visible on high traffic pages of a content site as opposed to ad slippage on an esoteric search results page. Further, without careful consideration, a black list may be over-inclusive and block ads with an objectionable keyword but in an adjacent category. For example, it may be desired to block ads for Sony consumer electronics, but if “Sony” is added to the blacklist, ads for Sony DVDs may be inadvertently blocked.
In view of the foregoing, there is a need for better ad blocking techniques. Such techniques should meet one or more of the following goals: (i) be easy to set up; (ii) be easy to manage; (iii) avoid under-inclusion; (iv) avoid over-inclusion; and (v) work with content-targeted ad serving systems.